1. Field of the Invention
The invention is directed to an arrangement for predicting an abnormality of a system and for the implementation of an action opposing the abnormality.
2. Description of the Related Art
The determination of an information flow of a system is known from G. Deco, C. Schittenkopf and B. Schürmann, “Determining the information flow of dynamical systems from continuous probability distributions”, Phys. Rev. Lett. 78, pages 2345–2348, 1997 (Deco), and C. Schittenkopf and G. Deco, “Testing non-linear Markovian hypotheses in dynamical systems”, Physica D104, pages 61–74, 1997 (Schittenkopf).
The information flow described in these references characterizes a loss of information in a dynamic system and describes decaying statistical dependencies between the entire past and a point in time that lies p steps in the future as a function of p. Among other things, the utility of such an information flow is that a dynamic behavior of a complex system can be classified, allowing a suitable parameterized model to be found that enables a modelling of data of the complex dynamic system.
A neural network and the training of a neural network are known from J. Herz, A. Krogh, R. Palmer, “Introduction to the Theory of neural computation”, Addision-Wesly, 1991 (Herz).